A Review of Differentiable Simulators
Differentiable simulators continue to push the state of the art across a range of domains
including computational physics, robotics, and machine learning. Their main value is the …
including computational physics, robotics, and machine learning. Their main value is the …
H2O+: an improved framework for hybrid offline-and-online RL with dynamics gaps
Solving real-world complex tasks using reinforcement learning (RL) without high-fidelity
simulation environments or large amounts of offline data can be quite challenging. Online …
simulation environments or large amounts of offline data can be quite challenging. Online …
Obstacle avoidance shape control of deformable linear objects with online parameters adaptation based on differentiable simulation
C Ying, K Yamazaki - ROBOMECH Journal, 2024 - Springer
The manipulation of deformable linear objects (DLOs) such as ropes, cables, and hoses by
robots has promising applications in various fields such as product assembly and surgical …
robots has promising applications in various fields such as product assembly and surgical …
[PDF][PDF] A Review of Differentiable Simulators
A COSGUN - 2024 - dro.deakin.edu.au
Differentiable simulators continue to push the state of the art across a range of domains
including computational physics, robotics, and machine learning. Their main value is the …
including computational physics, robotics, and machine learning. Their main value is the …